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About

Xiaosong Li is a researcher specializing in computer vision, structured-light sensing, and autonomous robotic systems, with contributions spanning visual navigation, sensor calibration, and robotic perception. His most impactful work, "A Robust Laser Stripe Extraction Method for Structured-Light Vision Sensing" (2020, 28 citations), addresses a critical challenge in environmental sensing for unmanned vehicles and robots, offering an innovative, cost-effective alternative to expensive multi-line LiDAR systems in low-light conditions. This contribution has resonated strongly within the robotics and autonomous systems community. Li has further advanced sensor fusion research through his work on camera-IMU extrinsic calibration, tackling the practical challenge of timing delays in visual-inertial navigation systems. His pipeline inspection research demonstrates a commitment to real-world industrial applications, developing multi-directional structured-light sensors mounted on robots for precise inner-surface 3D measurement. Beyond rigid robotics, Li has also explored soft robotics, designing an inchworm-inspired crawling robot using bidirectional bending actuators. Collectively, his work reflects a versatile and applied research vision, bridging low-cost sensing innovation with intelligent robotic systems across both autonomous navigation and industrial inspection domains.